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Knapsack Problem

Archive contents

  • raport.pdf - PDF documentation of the project
  • raport.tex - LaTeX code for the pdf
  • img - Folder containing the graphs
  • other - folder containing old implementations
  • src - folder containing the source files, tests and their results
  • utils - folder containing the benchmark

Tests Documentation

Tests are generated with the script tests_gen.py. There are 28 tests of sizes specified in the ns array, ranging from size 20 all the way up to 90. Initially I had bigger input sizes, but the backtracking solution would take forever. 2 more tests are used from an online resource documented in the References section of the pdf file. The maximum capacity of the knapsack is generated randomly between max_weight // 2 (max_weight is a 1000, but it can be changed fairly easy) and max_weight. The weights of the objects are randomly generated between 1 and half of max_weight and the values between 1 and 1000. More info about the tests and their results is written in the pdf file.

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The analysis of different algorithms that solve the knapsack problem. Google benchmark C++

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